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同震崩塌滑坡的光学遥感影像多特征融合解译方法
引用本文:韩征,方振雄,傅邦杰,吴斌晖,李艳鸽,李常丽,陈光齐.同震崩塌滑坡的光学遥感影像多特征融合解译方法[J].中国地质灾害与防治学报,2022,33(6):103-113.
作者姓名:韩征  方振雄  傅邦杰  吴斌晖  李艳鸽  李常丽  陈光齐
作者单位:1.中南大学土木工程学院,湖南 长沙 410075
基金项目:国家重点研发计划专项(2018YFC1505401);国家自然科学基金面上项目(52078493);湖南省自然科学基金优秀青年项目(2021JJ20057);湖南创新型省份建设专项经费资助项目(2020RC3002);长沙市科技计划项目(kq2106018)
摘    要:同震崩塌滑坡的解译及定位是震区灾后恢复工作中需要重点解决的问题,如何在灾害快速、自动解译的基础上,不断提高解译精度,是目前同震崩塌滑坡解译的研究热点之一,也是促使地质灾害早期识别向智能化、科学化发展的必要前提。文章在团队前期所提出的遥感影像局部阈值二值化方法的基础上,针对同震崩塌滑坡解译结果假阳率偏高的问题,分析了假阳性地物的光学和几何特点,提出了融合目标区域光学影像灰度特征、区域坡度信息、NDVI指数特征及解译地物主轴特征的同震崩塌滑坡多特征融合解译方法。为验证所提出模型的准确性,以2014年云南鲁甸地震龙头山镇为研究区,利用震后获取的高分一号(GF-1)卫星影像数据及数字高程模型对该同震崩塌滑坡进行了解译识别,结果表明,文中提出的方法准确解译出了同震崩塌滑坡区域,并有效去除了假阳性地物干扰,提高了解译精度。

关 键 词:遥感影像解译    同震崩塌滑坡    二值化分割    多特征策略    蒙特卡洛迭代
收稿时间:2021-11-03

Interpretation method for regional co-seismic collapses based on multi-feature fusion of optical remote sensing
Institution:1.School of Civil Engineering, Central South University, Changsha, Hunan 410075, China2.Key Laboratory of Hunan Province for Structural Disaster Prevention and Mitigation of Rail Transit Engineering, Changsha, Hunan 410075, China3.Key Laboratory of Heavy-duty Railway Engineering Structure, Ministry of Education, Changsha, Hunan 410075, China4.Kyushu University School of Engineering, Fukuoka 819-0372, Japan
Abstract:Interpretation of co-seismic collapse landslides is a key problem that needs to be solved in the post-disaster recovery work in earthquake areas. The issue regarding continuously improvement of interpretation accuracy for rapid and automatic interpretation of disasters is currently a hot topic, which is also a prerequisite to promote the development of early recognition of geological disasters towards intelligence and scientific. Based on the local threshold binarization method of remote sensing image proposed by the team in the early stage, this paper analyzes the optical and geometric characteristics of false positive features and proposes a fusion for the high false positive rate of the interpreted results of co-seismic mountain collapse. The multi-feature fusion interpretation method of the co-seismic mountain collapse with the gray feature of the optical image of the target area, the regional slope information, the NDVI feature and the interpretation of the main axis feature of the ground feature. In order to verify the accuracy of the proposed model, based on the 2014 Ludian earthquake in Yunnan, a case study was carried out in the Longtoushan town area. The Gaofen-1 (GF-1) satellite image data obtained after the earthquake and the digital elevation model were used for the earthquake in this area. The interpretation and recognition of the collapse of the cracked mountain shows that the method proposed in this paper accurately interprets the collapsed area of the cracked mountain body, effectively removes the false positive ground object interference, and improves the accuracy of interpretation.
Keywords:
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